What It Really Takes to Become an AI Growth Strategist
Why It Matters
Rooster Sanchez breaks down the shift from media buyer to AI growth strategist into four core skills: context engineering, skills stacking, connectors, and being the "point person" who actually drives AI adoption into daily team workflow.
Context beats tooling every time. Feeding AI the brand's historical wins, voice, and client quirks matters more than any new connector or automation, skip it and everything downstream is generic or wrong.
Connectors plug AI into live data (Shopify, GA, email, ad platforms, even meeting notes) instead of stale PDFs. Rooster's team dumps meeting notes straight into the model, which he calls the single biggest unlock for client comms.
Cohort, LTV, and product-level profit analysis that used to require a data scientist and two days of work now comes together in a single morning Slack digest.
The eliminate-before-automate filter is the sharpest idea here: before building AI around any SOP, ask if the process is even necessary. Automating a pointless workflow just wastes time faster.
Tactical specifics covered include building a "card" per client so AI knows how each wants to be reported to, an alert stack for creative fatigue and CPM spikes, a folder structure for finding things fast across a client roster, and a prompt designed to stop AI from being sycophantic.
One reframe worth sitting with: the number one reason clients churn has nothing to do with performance, which changes what an AI growth strategist should actually be optimizing for.
Who This Is For
This is a practical roadmap for Foxwell Founders members thinking about evolving their own role, or their team's, from campaign execution into AI-forward strategy. If you're a media buyer or account lead wondering what to actually build (context libraries, client cards, connector stacks) versus what to skip, Rooster's framework gives a concrete starting point. It's especially relevant for Founders members managing multiple client accounts who want AI catching problems before a client has to point them out.
If you work in DTC and you use AI, it seems like every week there’s a new tool, tactic, or workflow promising to make your job easier or threatening to replace you and your team. But what does it actually mean to evolve from a traditional media buyer or account lead into an AI growth strategist? And what are the real skills you need to make that leap?
Andrew Foxwell sat down with Thomas Moen and Rooster Sanchez to get into the weeds on all things AI with regard to a growth strategist role. Here’s what we learned (and what you can start doing right now).
What is an AI Growth Strategist?
This is the person with their hands on the whole funnel (numbers, creative, reporting, etc.) who uses AI at every step. This role isn't just launching campaigns; they're making sure the whole machine is running smoothly.
Rooster broke it down into four core skills an AI growth strategist needs to master:
Context Engineering: Making sure your AI models really know the business. Feed the AI tools the data, brand context, and historical nuance they need to produce relevant, high-quality outputs. Skip this and everything else falls apart.
Skills (and Skills Stacking): Building out an AI “skills stack” lets you automate or enhance the tasks you do most often, so you’re not constantly reinventing the wheel.
Connectors: Plug the models into live data. AI thrives on fresh, real-time inputs, whether that’s Shopify, Google Analytics, or your meeting notes.
Point Person: An AI growth strategist should be the person who actively pushes AI into the team’s workflow. This role is about being the driver who makes sure these systems are used in the real world, day in and day out.
Master these four skills, and you’ll turn projects that once required a data scientist and two days of focused effort into insights delivered in a single morning Slack digest.
An AI Growth Strategist's Playbook
Rooster shared why getting your context right comes before any fancy tools, which connectors he thinks are absolutely non-negotiable, and how his team went from two-day strategy lockouts to simple, actionable Slack digests every morning. Maybe even more importantly, he explained why eliminating unnecessary processes is always better than simply automating them.
Here are some of the practical things he covered:
What an AI growth strategist owns that a media buyer or account manager doesn’t
The four foundational skills: context, skills, connectors, and being the point person
Why you no longer need a data scientist for cohort, LTV, and product-level profit analysis
The folder structure that makes Claude find things faster across a whole client roster
Why migrating meeting notes into the model was the single biggest unlock for client comms
Building a card per client so AI knows how each one wants to be reported to
The must-have connectors for a growth role, and where Google Meridian fits for larger accounts
The alert stack: creative fatigue, audience saturation, CPM spikes, net new reach drops
Why the number one reason clients churn has nothing to do with performance
Elimination before automation, and how to run your SOPs through that filter
Logging every scheduled task so AI spots trends across your whole client base
The prompt that stops AI from being sycophantic, and what it reveals
Why every landing page now looks the same, and why that makes brand a moat
Building your own context libraries and client cards? Founders members are trading what's actually working inside their AI stacks.
Why Context Beats Tooling (Every Single Time)
Before you get excited about the newest connector or automation, remember: the context you give your models is the single biggest predictor of success. If your AI doesn’t know your historical wins, your brand voice, or your client’s quirks, it’ll spit out generic (or potentially incorrect) advice. Rooster’s team spends real time building context libraries, so every output is sharp, on-brand, and ready to act on.
The Power of Real-Time Data
Connectors are essential to a modern growth strategist's work and are much preferred by AI over a static PDF or other onboarding document that hasn't been updated in many months or years. Plug the real-time data into a connector and connect it into Shopify, Google Analytics, email and ad platforms, even your meeting notes. Rooster’s team set up flows that dump meeting notes straight into the AI, unlocking new insights and keeping everyone aligned. (Pro tip: Google Meridian is game-changing for big accounts.)
Eliminate, Then Automate
Before you automate any process, pause and ask whether it's truly necessary in the first place. Often, the most efficient workflow is eliminating unnecessary steps entirely. Ruthlessly evaluate every SOP with a simple question: “Is this really needed?” Only then should you consider building AI or automation around it. Automating a pointless or outdated process just makes it more efficient at wasting time.
The Big Takeaway
If you’re still treating AI like an add-on to your old workflow, you’re missing the real opportunity. Building and being a business that is AI-forward means the AI Growth Strategist is putting in the work on context, stacking up skills, connecting AI tools to live data, and being the one who brings it all together for your team and your clients.
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